Human Interaction with Data

“Meaningful Interpretations”

“The Power of Crowdsourcing”

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Introduction

Data

Knowledge and Decisions

Analysis

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Human Interactions with Data

“Meaningful Interpretations”

“Meaningful Interpretations”

Raw Data Information

Data Visualization and Exploration

http://mbostock.github.io/d3/talk/20110921/#24

Leveraging Human Input in Data Analysis“Crowdsourcing”

(1) harnessing the efforts of individuals to accomplish a larger task.

(2) process of obtaining data from groups either explicitly (deliberate contributions to a site or resource) or implicitly (side-effect of other activity).

“The Power of Crowdsourcing”

Example types of crowdsourced systems: User-generated content sites

users CRUD pages of information on a variety of topics

Question-answering systems experts answer questions regarding respective discipline

Massive multi-player online games used in encouraging contribution in solving specific types of problems

Collaborative analysis enables dissemination and discussion of data to detect/understand trends

“The Power of Crowdsourcing”

Leveraging Human Input in Data Analysis

Two Modes of Crowdsourcing1.Leveraging Human Activity

- Analyzing behavior- Source of data

2. Leveraging Human Intelligence - Solving Problems - Source of analysis

“The Power of Crowdsourcing”

Leveraging Human ActivityObservation of large-scale human behavior can can be a great source of data that can potentially answer many questions. This is essentially crowdsourcing data collection.

“The Power of Crowdsourcing”

Leveraging Human IntelligenceHumans have ability to discern complex patterns by incorporating subjective perceptions (such as context). Crowdsourcing can allow us to “teach” computers to recognize patterns, as well as improve current algorithms and analyses.

“The Power of Crowdsourcing”